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Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
Lu, G. et al University of Pittsburgh
Aug 30, 2024
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
Alternative CAES Technology Using Depleted Unconventional Gas Wells and Subsurface Thermal Energy Storage (GeoCAES)
This project assessed the technical viability of a process called GeoCAES. The process stores electrical energy by injecting natural gas into shale gas formations using a compressor, storing it, and producing it through an expander to generate electricity. This data submission inc...
Johnston, H. and Young, D. National Renewable Energy Laboratory
May 23, 2019
8 Resources
0 Stars
Publicly accessible
8 Resources
0 Stars
Publicly accessible
Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
Mustafa, A. et al Battelle Memorial Institute
Sep 28, 2023
3 Resources
0 Stars
Curated
3 Resources
0 Stars
Curated
Appalachian Basin Play Fairway Analysis Thermal Risk Factor and Quality Analyses
*This submission revises the analysis and products for Thermal Quality Analysis for the northern half of the Appalachian Basin (https://gdr.openei.org/submissions/638)*
This submission is one of five major parts of a Low Temperature Geothermal Play Fairway Analysis. Phase 1 of the...
Jordan, T. Cornell University
Aug 02, 2016
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Stanford Thermal Earth Model for the Conterminous United States
Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....
Aljubran, M. and Horne, R. Stanford University
Mar 14, 2024
9 Resources
1 Stars
Curated
9 Resources
1 Stars
Curated